Brand Ambassador - Broadway Memorabilia Plus

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• ElevatedNY

  

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• Skyline Strategies

  

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• Cabu Latte

  

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• MassMutual

  

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  Model Validator Model Validations Team, Insurance, Product & Model Risk Full Time Springfield, MA, Boston, MA or New York, NY The Opportunity As a member of the Enterprise Risk Management (ERM) organization at MassMutual, you will partner with various business areas to conduct independent model validations for a wide variety of models, integral to critical business decision making, product pricing, financial reporting, risk mitigation activities and business processes. The Team The Model Validations team is comprised of seasoned professionals with expertise in actuarial, financial, risk, investment and capital markets models, who are also building knowledge in emerging areas of importance, such as data science, machine learning and artificial intelligence. The team conducts independent validations on a wide variety of models to ensure the company’s models are conceptually sound and performing as expected. The Impact You will utilize your actuarial, investment, and capital risk modeling expertise to conduct best-practice model validation activities, helping protect the company’s reputation and financial stability through robust management of risks associated with the use of these models. If you are someone that has a passion for complexity, continuous improvement, learning and curiosity about different points of view, this may be the right role for you. Specific expectations from this role: * Build relationships, influence, collaborate and learn various aspects of our business from many modelers, data-scientists, actuaries and business leaders at MassMutual. * As a risk advisor, participate in the design, development and implementation of new models * Conduct model validations in accordance with corporate model governance policy requirements and timelines, leveraging deep modeling, asset pricing, actuarial and regulatory expertise. * Assess model design, theoretical construction, methodology, applicability, and resilience within evolving economic and risk environments, in accordance with corporate, actuarial and/or regulatory standards. * Validate accuracy of model calculations, algorithms, and any embedded automation / programming code base. * Design and implement tests to ensure model performance and model output are as expected. * Prepare and distribute model validation documentation, which meets model governance requirements. * Test remediation of validation findings. * Continuously research and provide guidance on the use of new and innovative analytical techniques. The Minimum Qualifications * Bachelor’s degree in Actuarial Science, Finance, Econometrics, Statistics, Mathematics, Physics, or another quantitative discipline * 5+ years of direct experience in one of the following: * Capital markets and/ or investment risk * Quantitative asset pricing models * Liability hedging strategies * Statistical methods of analysis * 3+ Microsoft Excel, Access, and VBA * 3+ experience with Python The Ideal Qualifications * Possess one or more of the following designations * Associate of Society of Actuaries (ASA) * Fellow of Society of Actuaries (FSA) * Charter Financial Analyst (CFA) * Certificate in Quantitative Finance (CQF) * Financial Risk Manager (FRM) * 7+ years of direct experience in one of the following: * Capital markets and investment risk * Quantitative asset pricing models * Insurance liability hedging strategies * Statistical methods of analysis * ALM and annuity product pricing experience * Knowledge of commercial software, including Prophet, GGY AXIS and Moody's asset models * Strong statistical, risk, analytical, modeling, and problem-solving skills * Ability to see the big picture with meticulous attention to detail * Strong communication and collaboration skills, both written and verbal * Demonstrated accountability and ownership of self-development * Ability to build and maintain strong working relationships within and across teams, while challenging in a constructive manner * Strong execution and time management skills What to Expect as Part of MassMutual and the Team * Regular meetings with the Model Validations Team * Focused one-on-one meetings with your manager * Access to mentorship opportunities * Networking opportunities including the Actuarial Gathering, access to Asian, Hispanic/Latinx, African American, women, LGBTQ, veteran and disability-focused Business Resource Groups * Access to learning content on Degreed and other informational platforms * Your ethics and integrity will be valued by a company with a strong and stable ethical business with industry leading pay and benefits #LI-ST1 MassMutual is an equal employment opportunity employer. We welcome all persons to apply. If you need an accommodation to complete the application process, please contact us and share the specifics of the assistance you need.

• Amazon Web Services, Inc.

  

  Senior Applied Scientist, Model Customization, Generative AI Innovation Center, Model Customization

  4 days ago

  New York

  Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. Starting in 2024, the Innovation Center launched a new Custom Model and Optimization program to help customers develop and scale highly customized generative AI solutions. The team helps customers imagine and scope bespoke use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop and optimize models to power their solutions, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Applied Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities As an Applied Scientist, you will • Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges, • Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production, • Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization, • Provide customer and market feedback to product and engineering teams to help define product direction About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve. • PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field plus 5 years of relevant experience, or Master’s degree plus 10 years of relevant work experience, • 5+ years of hands on experience with Python to build, train, and evaluate models, • 5+ years of experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, • 2+ years demonstrated experience with Large Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniques., • Scientific publication track record at top-tier AI/ML/NLP conferences or journals, • Demonstrated experience with building LLM-powered agentic workflow, orchestration, and agent customization, • Experience with model optimization techniques (quantization, distillation, compression, inference optimization etc.), • Experience with open-source frameworks for model customization like trl, verl, and for building LLM-powered applications like LangChain, LlamaIndex, and/ or similar tools, • Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts, • Demonstrated ability to identify and frame technical problems from broad product-level and business-level problem areas., • Track record of leading the design, implementation and delivery of scientifically-complex solutions that span multiple teams., • Experience driving scientific agenda and technical strategy in a team, including building consensus on technical approaches and mentoring other scientists to improve their technical capabilities. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit ___ for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit ___. This position will remain posted until filled. Applicants should apply via our internal or external career site.